Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche 'STEBICEF', University of Palermo, Viale delle Scienze - Ed. 17, 90128 Palermo, Italy.
Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche 'STEBICEF', University of Palermo, Viale delle Scienze - Ed. 17, 90128 Palermo, Italy.
Drug Discov Today. 2021 Oct;26(10):2431-2438. doi: 10.1016/j.drudis.2021.05.013. Epub 2021 May 26.
Matching biological data sequences is one of the most interesting ways to discover new bioactive compounds. In particular, matching cell chemosensitivity with a protein expression profile can be a useful approach to predict the activity of compounds against definite biological targets. In this review, we discuss this correlation. First, we analyze case studies in which some known drugs, acting on known targets, show a good correlation between their antiproliferative activities and protein expression when a large panel of tumor cells is considered. Then, we highlight how the application of in silico methods based on the correlation between cell line chemosensitivity and gene/protein expression patterns might be a quick, cheap, and interesting approach to predict the biological activity of investigated molecules.
匹配生物数据序列是发现新的生物活性化合物的最有趣方法之一。特别是,将细胞化学敏感性与蛋白质表达谱相匹配可以成为预测化合物对特定生物靶标活性的有用方法。在这篇综述中,我们讨论了这种相关性。首先,我们分析了一些案例研究,其中一些已知的药物,作用于已知的靶点,在考虑大量肿瘤细胞时,其抗增殖活性与蛋白质表达之间显示出良好的相关性。然后,我们强调了基于细胞系化学敏感性与基因/蛋白质表达模式之间相关性的计算方法的应用如何成为预测所研究分子的生物学活性的快速、廉价和有趣的方法。